Local verification systems and methods for security monitoring

ABSTRACT

A security monitoring system for reducing the number of false alarms through verification comprises a remote system at a first location remote from a second location and a local system located at the second location. The remote system comprises a remote database. The local system is electronically linked with the remote system to provide indication of alarm events to the remote system and comprises at least one camera operable to capture at least one image of a local object in view of the camera, a local database operable to electronically store at least one template corresponding to an authorized object, and an image processing system operable to perform a visual verification. The visual verification comprises comparing the at least one image of the local object with the at least one template corresponding to the authorized object and, if a matching result occurs from the visual verification, suppressing indication of an alarm event to the remote system.

FIELD

The disclosed technology relates to methods and systems regarding security monitoring and alarm system technology.

BACKGROUND

For years, security systems have employed video cameras and video processors that can perform some type of motion detection by watching for motion in a scene, generally by looking at differences between a current video frame and a previous video frame. If motion or motion exceeding a predetermined threshold is detected, an event is recognized. This event could create an alarm condition or trigger other actions, such as speeding up the capturing of images from the associated camera or storing captured images at a higher resolution or faster frame rate. Some security systems can be configured to distinguish different portions of the scene such that motion in some portions is considered more important then in other portions.

False alarms have become a significant drain on resources for police departments. More than 90% of all alarms sent to central alarm monitoring stations are false alarms. Moreover, more than 90% of all alarms sent to police departments are false alarms, and a significant portion of these false alarms were first screened by central alarm monitoring stations.

Some existing systems have video cameras mounted at both entries and exits to capture images of people entering and leaving the premises. Some of these systems or other systems may require that a camera be mounted on a door itself along with some type of sensor such as a doorknob sensor.

Current systems that have some type of visual verification do not perform any type of recognition at the premises but, rather, send video images to a remote central monitoring station for verification of alarms.

Certain existing alarm systems have motion detection techniques that involve the direct comparison of frames to detect motion and classify detected objects in the scene. In some of these systems, an alarm is only sent if the object is determined to be a human. Screening video based simply on whether detected motion is based on a certain class of objects (e.g., screening for humans) does not significantly reduce false alarms, if at all, because nearly all false alarms are caused by humans.

SUMMARY

Described herein are exemplary methods and systems for performing local verification in security monitoring applications. One advantage of using the described local verification approach is a reduced number of false alarms. Another advantage is the increased efficiency that comes with a system that performs verification on the premises before sending any information to a central monitoring station. The suppression of image information (e.g., video) to be transmitted for remote viewing in situations where such video need not be viewed by a third party (e.g., when an event is false) provides system users (e.g., homeowners) with the additional advantage of privacy.

In one embodiment, a security monitoring system includes a remote system and a local system, the local system being located at the premises being monitored. The local system includes cameras or other image capture devices to capture images of objects (e.g., video), a database that stores image templates corresponding to humans that are authorized to be on the premises, and a video processing system that can determine whether the object is human and, if so, can perform a visual verification by comparing the captured images with the image templates stored in the database. If a positive match occurs, then the object is deemed a human authorized to be on the premises and any alarm event indication is suppressed. If there is no positive match, however, or if no comparison can be made, a prioritization level is determined and transmitted along with the video clip to the remote system for further analysis. The remote system includes an image database that stores images of people authorized to be on the premises such that the image templates used by the local system do not need to be transmitted to the remote system.

In another embodiment, a method of reducing false alarms in a security monitoring system monitoring a location remote from a central monitoring system, where a communications link exists between the two systems, includes detecting a conditional alarm-generating event based on presence of an object at a premises associated with the monitored location. The exemplary method also includes capturing image data corresponding to the object and determining at the monitored location whether the object is authorized, based on a comparison between the captured image data and electronically stored templates. If a positive match results from the comparison, an alarm event notification to a remote system is suppressed.

In yet another embodiment, a verification module of a local component of a security system configured to communicate with a remote component includes an electronic circuit with a processor operable to perform a verification based on a comparison of at least one image of a monitored local scene and stored reference data. The verification module determines autonomously whether to indicate an alarm event. Based on the comparison results, if the image is determined not to match the reference data, an alarm event is recognized and the local component communicates the alarm event to the remote component. If the at least one image is determined to match the reference data, however, an alarm event is not recognized and no alarm event communication to the remote component occurs.

The foregoing and other features and advantages will become more apparent from the following detailed description, which proceeds with reference to the accompanying figures.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram illustrating an exemplary security system with a local system configured for visual verification linked to a remote system.

FIG. 2 is a flowchart illustrating an exemplary method for performing visual verification within a security monitoring system.

DETAILED DESCRIPTION

Described below are embodiments of a security system and methods in which visual verification of events occurring at a monitored scene at a first location takes place prior to triggering an alarm event at a remote system at a second location. In described embodiments, the visual verification is accomplished using electronic video surveillance equipment. In described embodiments, the visual verification can be configured to take place autonomously without active participation by operators at the first location or second location. In described embodiments, the verification typically involves the use of image information, e.g., visual information such as video, although other types of information (e.g., audio information) can also be used. In some embodiments, the image information can be infrared image information.

If visual verification of an event at a monitored scene is initiated, possibly in response to a sensed condition, the system evaluates whether the monitored scene exhibits characteristics of an alarm event, e.g., the system can evaluate scene changes. In described embodiments, the system evaluates whether object(s) in the monitored scene correspond to or are sufficiently similar to authorized objects (e.g., persons and/or pets authorized to be present at the first location).

This evaluation includes comparison with stored representations of such authorized objects, e.g., templates. If the comparison shows that the object(s) correspond to or are sufficiently similar to authorized objects, and thus the object(s) is considered authorized, no alarm event is triggered. If, however, the visual verification fails or is inconclusive, the remote system can communicate an alarm event indication to the remote system.

In some embodiments, the remote system subjects the alarm event conditions at the first location to further review or validation, such as, e.g., by an operator. Conveniently, the local system can be configured to provide one or more images and/or other information (e.g., the closest templates) to assist in validating the alarm event. Thus, many false alarms initiated by authorized objects can be addressed before involving the remote system. In addition, some alarm events that are communicated quickly and with greater accuracy because additional alarm event conditions information (e.g., video clips, closest match-ups, etc.) can be provided.

FIG. 1 illustrates an exemplary embodiment of an automated visual verification security monitoring system 100. The system 100 includes two exemplary sub-systems: a local system 120 (e.g., at a monitored premises) and a remote system 150 (e.g., at a central monitoring facility). The monitored premises can be, for example, a building (e.g., a home, commercial building, other type of structure, etc.) or other type of premises where verifying alarms is of interest.

The local system 120 has multiple cameras 102A-102N, multiple alarm sensors 104A-104N, an optional microphone 106 and speaker 107, and an image processing unit, such as a video processing unit 108. Image-capturing devices other than cameras can be used in place of, or in addition, the cameras 102A-102N.

The alarm sensors 104A-104N can be, for example, typical motion detectors or door and window sensors. In this example, the sensors 104A-104N are motion sensors that are each mounted with the cameras 102A-N, respectively, in pairs. Each camera/sensor pair can be mounted in a single housing to facilitate and expedite the processing of video images from a particular camera upon the detection of motion by the corresponding sensor. The number of cameras and/or sensors, as well as their arrangement within a system, however, can all vary greatly.

In certain embodiments of the disclosed technology, cameras can be mounted either just inside or just outside doors to the premises (e.g., a home). In arrangements where the cameras are mounted inside the doorway, they are typically aimed at the door itself to capture images of people's faces upon entry through the doorway. In arrangements where the cameras are mounted outside the doorway, they are typically mounted near the doorbell to capture images of the faces of those approaching the door. These cameras can also see people leaving through the doorway though their faces might not be in full view. Cameras mounted near the doorbell also generally provide for easier wiring of power and communication lines to the cameras. It is desirable that the cameras have a wide dynamic range so that they can provide good images for the video processing unit 108 even if there is a bright light behind a person approaching a door if the camera is on the outside or, if the camera is on the inside, when the door opens.

The cameras do not need to be mounted both inside and outside a door because, for example, the video recognition system described herein can recognize people by their appearance and not just their faces. For example, the local system 120 of FIG. 1 can have stored representations of authorized objects, e.g., an image template database 110 that stores image templates that can be used to recognize people that are authorized to be on the premises. Such image templates can be created, for example, by the local system 120 itself or through a manual enrollment process (e.g., at a commercial location). The video processing unit 108 can determine most likely matches by comparing captured images of the person in question with the image templates stored in the image template database 110.

The cameras do not need to be mounted on a door itself. This is advantageous because providing electrical power for a camera at the location of the door is usually difficult.

The local system 120 can be configured to begin processing of video images after the occurrence of a sensed condition (e.g., upon the tripping of a door or window sensor). In other embodiments, a camera itself can recognize motion or the opening and/or closing of windows and doors by itself without external sensors. In other embodiments, processing of video images occurs regardless of any sensed conditions.

FIG. 2 illustrates an exemplary method for performing visual verification within a security monitoring system, such as the system 100 of FIG. 1. At 202, a video clip of an object (e.g., a possible intruder on the premises) is captured, such as by one or more of the cameras 102A-102N. At 204, an analysis is performed to determine whether the object is human. If so, the system then performs a visual verification that includes comparing an image template corresponding to the object in the captured video clip with stored image templates, as shown at 206. If not, the system suppresses an alarm event notification, as shown at 208.

If a positive match is found at 206, the object has been identified as a human considered to be authorized, so any alarm event indication is suppressed. A positive match does not require an identical match but is understood to include a reasonable match, which can be set according to the specific operating characteristics. In some embodiments, a threshold can be set for determination of whether a match should be considered positive. If no match is found, however, or if the system is unsure, an alarm event is recognized. According to one approach, a prioritization level is generated, as shown at 210.

The prioritization level is transmitted with the captured video clip from the local system to the remote system, as shown at 212, such that an operator at a central monitoring facility, for example, can analyze the video clip to determine whether the alarm event is valid. If an object is unable to be subjected to a comparison (e.g., there are no templates corresponding to the object's type), a potential alarm event can be indicated to the remote system. In such a situation, review by security personnel would usually be desirable.

The video processing unit 108 of FIG. 1 can include various modules, such as those described in U.S. Pub. No. US 2005/0002572 A1 to Saptharishi et al., filed Jul. 1, 2004, which is hereby incorporated by reference. For example, a foreground/background separation module can receive an input signal and, according to one or more adaptable parameters, produce as output foreground/background labels designating elements of the input as either foreground or background elements. A foreground object grouping module can identify groups of selected foreground-labeled elements as foreground objects. An object classification module can generate object-level information related to the foreground object. The object-level information can adapt the one or more adaptable parameters of the foreground/background separation module via a feedback connection.

The video processing unit 108 has the ability to distinguish humans from other forms of video motion, such as animals, changes in lighting, headlights, balloons floating in the air, and trees blowing in the wind. The video processing unit 108 can also distinguish one human from another by visual features such as hair color, height, clothing, etc. The video processing unit 108 can also use facial features commonly used in facial recognition systems.

When a person leaves through a door, the local system 120 can recognize that person by his or her features, such as clothing, hair, height, etc. If that person should re-enter the premises shortly afterward, he or she would be recognized and allowed to enter without the generation of an alarm. This eliminates another common cause of false alarms, such as when people go outside their house to get the mail or the newspaper and forget that their system is armed. Such a feature can be programmed such that anyone leaving their home is automatically allowed back in within a preset period of time. That time period could be e.g., a whole day or a much more limited time (e.g., 15 minutes).

Another advantageous feature of the disclosed technology is the ability to recognize a person more accurately with facial recognition or by other biometric features that do not change with clothing or hair style. The local system 120 can store tokens or templates of data (e.g., in the image template database 110) that represent the person's biometric features, such as facial features, for all people authorized to enter the premises. When a person is seen entering or leaving through one of the doors to the premises, their images can be reduced to a token or template by the video processing engine, which then compares it to those in the image template database 110 that correspond to authorized people. If an appropriate match is obtained, then the likelihood of an alarm is low but further verification might still be desired before the alarm is ignored. For example, the person can still be required to enter their passcode at a keypad. His or her passcode can then be compared to the image of the person authorized to use that passcode. The local system 120 can have a locking system that only opens with the proper access control card being presented to a reader. This could also identify the person opening the door. Therefore, the facial recognition might only verify the person entering, or it might be used as the only means of recognition, for example in homes where only a few people are authorized and the system is capable of accurately recognizing those few.

The video processing unit 108 screens out and suppresses false alarms that might otherwise be transmitted to the remote system 150. Thus, it can be determined at the premises whether an alarm event is potentially valid or false and, if the alarm event is determined to be false, an alarm is not ultimately generated. In situations, however, where the alarm event is determined to be real or the video processing unit 108 is uncertain, the captured video clip can be transmitted to the remote system 150, and, in some embodiments, with a prioritization level. Such a prioritization level is generally based upon predetermined criteria and usually includes a brief description of what a user (e.g., a security guard) at the remote system should consider in reviewing the transmitted information. The prioritization level can help such a user rank the most likely alarm events as a higher priority for response as opposed to alarm events that appear to be less likely to be valid. For example, an unknown intruder might have a high priority whereas a door opening with no people present might warrant someone inspecting the situation but not on an immediate basis.

When the video processing unit 108 is unable to adequately match the captured images with the stored image templates, it can transmit a captured video clip of the person along with a list of possible matches. Such a list generally represents the best possible matches. Optionally, the remote system 150 can include an image database 152 that stores images of people that are authorized to be on the premises, in which case the image templates used at the local system 120 do not need to be sent to the remote system 150 each time video clips are transmitted for review. For example, names of authorized people that appear to be similar to the intruder can be sent to the remote system 150 and images corresponding to those names can be retrieved from the image database 152 and displayed (e.g., using a monitor 154) along with the transmitted video clip to allow for a user of the remote system to compare the images to the video clip. This method is advantageous because it reduces the amount of data to be transmitted from the local system 120 to the remote system 150 and it reduces the number of authorized people to be compared to the transmitted video clip. This is important in situations where there is a large list of people authorized to be on the premises. This method also provides for increased transmission speed, which can be significant in setups where communication takes place via a dialup connection.

In one example, in which door switches are used, video images are processed upon the opening of the door to see if someone was walking toward the door from the inside (if the camera is inside) or walking toward the door from the outside (if the camera is outside) before the door opened. The system can also analyze the video to determine whether someone was inside or outside the doorway after the door closed again.

In another example, in which motion detectors are used, video images are processed upon the detection of motion in the field of view, including the door, to see whether the first motion was the opening of the door or a person approaching the door. A video camera that is being processed continuously can recognize motion to trigger this same event instead of the use of an external motion detector. When a person is seen to be leaving the home or premises, any alarms that might normally be generated by the door opening or the motion sensors can be ignored. This eliminates a common cause of false alarms. The local system 120 can recognize the difference between animals, such as pets, and humans or other common causes of video motion, such as lights and shadows. This is advantageous because, for example, stray light (e.g., headlights from a passing car or sunlight that is intermittently blocked by clouds) shining through the window could appear as if someone was on the inside near the door if only simple video motion detection was used.

If all of the entryways to a premises are being monitored, a count of people entering and leaving can be kept. Thus, the local system 120 can keep track of when everyone has left the premises or whether someone is still on the premises. When everyone has left, the local system 120 can respond differently to intruders than if someone is still present. For example, if everyone has left then, except for people coming in through one of the entryways, no person should be detected indoors. If a person is detected indoors after everyone has left but no one came in through any of the entryways, then the local system 120 can determine this to be a break-in. However, if someone comes in through a door, or even if they approach a door from the outside, and someone is still home or on the premises, then the local system 120 might announce this by ringing a bell or sounding a buzzer to alert the person inside that someone is approaching or has just entered the house or premises. For example, a small store might ring a bell in the back to alert someone that a person has entered the front door, but if the last person has left for the day, then such an event would trigger an alarm.

Another advantageous feature that can significantly reduce the number of false alarms is the use of an optional automated voice response function in the system that can be performed in real-time. If someone enters the system and is not sure this person is authorized, a prerecorded message can be played for the intruder. For example, the message might say: “Hello. This is the Protective Alarm Monitoring Center. Please state your name, followed by your passcode.” The system then records any audio responses (e.g., using a microphone 106). In one configuration, the local system 120 simply records this response and sends it in with any alarm data and/or video data of the intruder that is transmitted to the remote system 150. The remote system 150 can use this information to facilitate verification of the alarm, saving the monitoring operator from having to call back the premises after an alarm has been received to verify it. In many cases, it is not feasible or even possible for an operator to call back after an alarm has been received because either someone is on the phone or the alarm system itself is occupying the phone line by sending more data, such as video data.

Another advantageous feature of the disclosed technology is the ability to provide voice pattern matching, or voice recognition, to match the voice of the responder to a database of stored templates or voice tokens for authorized people. This can be compared to both the video templates stored and/or the passcode the person called out. This audio enunciation and listening can take place through a speaker (e.g., speaker 107 of FIG. 1) and microphone (e.g., microphone 106) mounted near the camera, or it can be accomplished by having the local system 120 ring the premise phones so that the person entering answers the phone. Over the phone the local system 120 can recite its voice message and listen to responses. The person could also enter their passcode through the phone keypad rather than verbally.

Automated voice recognition further reduces alarms from being sent to central monitoring stations when they are false and makes a self-monitoring system even more practical. The functions of central monitoring stations to call back the premises after every alarm would be accomplished automatically before the alarm was even generated. This also saves embarrassing situations with the end-users who often accidentally cause false alarms. The local system 120, if unsure about a response (e.g., due to the lack of an appropriate match with what is stored in the database for authorized people), can also initiate further questions to facilitate verification. For example, the system could ask the person's birthday or middle name, providing more information for the voice recognition system to better identify him or her. This provides a significant deterrent to potential intruders since the local system 120 will be recording their images and voices. The local system 120 thus provides the additional benefit that it puts less pressure on a person to get their code right and to enter it within a limited time.

One configuration of the disclosed technology can eliminate the need for a keypad for the entering of codes to disarm the alarm system and by using just video recognition, with audio recognition as a backup in situations where uncertainty exists. The person's clothing can be matched with what they wore that day when they left for work, for example. Alternatively, the person can use a keyfob transmitter to disarm the system with the touch of a button, and video recognition can be used to verify the person using the fob since each fob has a unique address.

With the exemplary system described herein, people can leave their home to go outside and get their newspaper or the mail, or go for a walk, and not have the worry about arming or disarming the system since the system would automatically remember their appearance as they left and know whether or not the premises is empty. Since a common cause of security system discontinuance is due to inconvenience and another common cause is the trouble with false alarms caused by inaccurately entering of the disarm code in the allotted time, the disclosed technology provides a much greater ease of use and improved protection to the person using it, while reducing false alarm signals and time spent at both central monitoring stations and the police force.

In view of the many possible embodiments to which the principles of the disclosed systems and methods may be applied, it should be recognized that the illustrated embodiments are only preferred examples and should not be taken as limiting in scope. Rather, the scope is defined by the following claims and all that comes within their scope and spirit. 

1. A security monitoring system for reducing false alarms through visual verification, comprising: a remote system at a first location remote from a second location, the remote system comprising a remote system database; and a local system located at the second location and electronically linked with the remote system to provide indication of alarm events occurring at the second location to the remote system, the local system comprising: at least one camera operable to capture at least one image of a local object in view of the at least one camera; a local database operable to store at least one template corresponding to an authorized object; and an image processing system operable to perform a visual verification, the visual verification comprising a comparison of the at least one image of the local object with the at least one template corresponding to the authorized object and, if a matching result occurs from the visual verification, to suppress indication of an alarm event to the remote system.
 2. The security monitoring system of claim 1, wherein the image processing system is further operable, if a matching result occurs from the visual verification, to suppress transmission of the at least one image of the local object from the local system to the remote system.
 3. The security monitoring system of claim 1, wherein the local object is a human being.
 4. The security monitoring system of claim 1, wherein the indication of an alarm event to the remote system is a provisional determination subject to validation by the remote system.
 5. The security monitoring system of claim 4, wherein the validation by the remote system comprises review of alarm event conditions by a human operator.
 6. The security monitoring system of claim 5, wherein the at least one image of the local object is transmitted from the local system to the remote system, and wherein the validation by the remote system comprises review of the at least one image by a human operator at the second location.
 7. The security monitoring system of claim 1, wherein, if the local object cannot be compared, the local system indicates a potential alarm event to the remote system.
 8. The security monitoring system of claim 1, wherein the image processing system performs object recognition and background/foreground analysis on the at least one image.
 9. The security monitoring system of claim 8, wherein the visual verification is performed in response to a determination that the local object is a foreground object.
 10. The security monitoring system of claim 1, wherein the remote system database is operable to electronically store at least one image corresponding to the authorized object.
 11. The security monitoring system of claim 1, wherein the image processing system is further operable, if a non-matching result occurs from the visual verification, to indicate an alarm event to the remote system.
 12. The security monitoring system of claim 1, wherein the image processing system is further operable, if a non-matching result occurs from the visual verification, to transmit an image clip comprising multiple images of the local object along with a prioritization level to the remote system
 13. The security monitoring system of claim 12, wherein the multiple images comprise a series of images taken in a defined interval.
 14. The security monitoring system of claim 12, wherein the multiple images comprise a series of sequential images.
 15. The security monitoring system of claim 12, wherein the multiple images show a scene before an alarm event.
 16. The security monitoring system of claim 15, wherein the multiple images further show the scene during the alarm event, and after the alarm event.
 17. The security monitoring system of claim 12, wherein the prioritization level is determined by the image processing system based on at least one predetermined criterion.
 18. The security monitoring system of claim 12, wherein the prioritization level comprises a representation of a degree of difference between the at least one image of the local object and the at least one template corresponding to the authorized object.
 19. The security monitoring system of claim 1, wherein the image processing system is further operable, if a non-matching result occurs from the comparison, to transmit at least one possible match for the local object based at least in part on results from the comparison.
 20. The security monitoring system of claim 1, wherein the local database is operable to electronically store at least one voice template corresponding to an authorized subject, and wherein the local system further comprises a voice verification system comprising: a device operable to capture a recording of a subject's voice; a voice processing system operable to perform an audio verification comprising an audio comparison of the recording of the subject's voice with the at least one voice template corresponding to the authorized subject and, if a matching result occurs, suppress transmission of the captured recording to the remote system.
 21. The security monitoring system of claim 20, wherein the audio comparison is performed in real-time.
 22. The security monitoring system of claim 20, wherein the voice processing system is further operable, if a non-matching result occurs, to transmit information resulting from the audio comparison to the remote system.
 23. The security monitoring system of claim 1, wherein the at least one camera comprises a plurality of cameras mounted inside a building, wherein the at least one camera has a visual range directed toward a doorway providing access to the building.
 24. The security monitoring system of claim 23, wherein the image processing system is further operable to determine whether the object is entering or leaving the building through the doorway.
 25. The security monitoring system of claim 1, wherein the at least one camera comprises a plurality of cameras mounted outside a building, wherein the at least one camera has a visual range directed away from a doorway providing access to the building
 26. The security monitoring system of claim 25, wherein the image processing system is further operable to determine whether the object is entering or leaving the building through the doorway.
 27. The security monitoring system of claim 1, wherein a non-matching result comprises a difference outside a predetermined range between the at least one image of the local object and the at least one template corresponding to the authorized object.
 28. The security monitoring system of claim 1, wherein the local system comprises at least one sensor operable to trigger the image processing system to perform the visual verification.
 29. The security monitoring system of claim 28, wherein the at least one sensor comprises a motion sensor operable to detect a moving object.
 30. The security monitoring system of claim 23, wherein the at least one template corresponding to the authorized object comprises biometric features of the human being.
 31. The security monitoring system of claim 23, wherein the image processing system is further operable to maintain a count of how many objects pass in or out the doorway during a given interval of time.
 32. The security monitoring system of claim 23, wherein the image processing system is further operable, if the object is determined to be re-entering the building within a predetermined time after leaving the building, to suppress transmission of the alarm signal to the remote system.
 33. The security monitoring system of claim 25, wherein the at least one template corresponding to the authorized object comprises biometric features of the human being.
 34. The security monitoring system of claim 25, wherein the image processing system is further operable to maintain a count of how many objects pass in or out the doorway during a given interval of time.
 35. The security monitoring system of claim 25, wherein the image processing system is further operable, if the object is determined to be re-entering the building within a predetermined time after leaving the building, to suppress transmission of the alarm signal to the remote system.
 36. In a security monitoring system having at least one monitored first location with a communications link to a central monitoring system at a second location remote from the first location, a method of reducing false alarms comprising: detecting a conditional alarm-generating event based on presence of an object at a premises associated with the first location; capturing image data corresponding to the object; determining at the first location whether the object is authorized, wherein the determining comprises performing a comparison at the first location of the captured image data to electronically stored templates; and if a positive match results from the performing of the comparison, suppressing an alarm event notification to a remote system.
 37. The method of claim 36, wherein a positive match comprises a reasonable match between the captured image data and at least one of the electronically stored templates.
 38. The method of claim 36, wherein if a positive match does not result, further comprising transmitting a video clip of the object to the remote system.
 39. The method of claim 37, wherein if a positive match does not result, further comprising transmitting a list of possible matches resulting from the performing of the comparison to the remote system along with a video clip of the object.
 40. The method of claim 36, wherein if a positive match does not result, transmitting an indication of an alarm event to the remote system.
 41. The method of claim 39, further comprising transmitting a prioritization level along with the video clip of the object, wherein the prioritization level is based at least in part upon a predetermined criterion.
 42. The method of claim 41, wherein the remote system comprises a central security monitoring facility.
 43. The method of claim 42, further comprising reviewing of the video clip of the object by a security advisor at the central security monitoring facility.
 44. The method of claim 36, wherein capturing image data comprises capturing video image data.
 45. A verification module of a local component of a security system configured to communicate with a remote component, the verification module comprising an electronic circuit with a processor operable to perform a verification based on a comparison of at least one image of a monitored local scene and stored reference data, the verification module determining autonomously whether to indicate an alarm event, wherein, based on the comparison results, if the at least one image is determined not to match the reference data, an alarm event is recognized and the local component communicates the alarm event to the remote component, and if the at least one image is determined to match the reference data, an alarm event is not recognized and no alarm event communication to the remote component occurs.
 46. The security system of claim 45, wherein valid verification of an intruder being an authorized owner/operator of the local system can provide the intruder with access to owner programming features.
 47. The security system of claim 45, wherein the reference data comprises a plurality of image templates.
 48. The security system of claim 45, wherein the at least one image is a video image. 